class_docstr: Class handler for using a ModelAgnosticEvaluation graph.
code: def __init__(
      self,
      add_metrics_callbacks: List[types.AddMetricsCallbackType],
      config: model_agnostic_predict.ModelAgnosticConfig,
  ):
      # Note that we do not actually initialize the graph here. The reason is we
      # wait until we get the first FeaturesPredictionsLabels to get
      # how the graph is to be constructed. Otherwise, we will need define a
      # config.
      self._add_metrics_callbacks = add_metrics_callbacks
      self._config = config
      super().__init__()
  
file_path: model-analysis/tensorflow_model_analysis/model_agnostic_eval/model_agnostic_evaluate_graph.py
imports: from typing import List, Optional
  import tensorflow
  from tensorflow_model_analysis.api import types
  from tensorflow_model_analysis.eval_metrics_graph import eval_metrics_graph
  from tensorflow_model_analysis.model_agnostic_eval import model_agnostic_predict
label_desc: Use image node_id 1 to create a new ModelAgnosticEvaluateGraph object from inherited base classes: eval_metrics_graph with example: obj = ModelAgnosticEvaluateGraph(add_metrics_callbacks, config)